Using artificial intelligence to analyze patient photos for chronic graft-versus-host disease
Official title: Artificial intelligence to estimate extent of cGVHD from patient photos
Funded at Vanderbilt University Medical Center · NIH-11081025 · Data updated 2026-11-12
This study is working on a smart computer program that can help patients with chronic graft-versus-host disease (cGVHD) by analyzing photos of their skin redness, making it easier and more affordable for them to get accurate assessments without always needing to see a doctor.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Vanderbilt University Medical Center NIH-funded |
| Lab location | 1 site (Nashville, United States) |
| Project start | May 1, 2024 |
| Project end | March 31, 2029 |
| Funding year | 2025 |
| Award (this year) | $677,620 |
| NIH project number | 5R01HL169944-02 |
| Project ID | NIH-11081025 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are patients who have undergone allogeneic hematopoietic stem cell transplantation and are experiencing symptoms of chronic graft-versus-host disease.
✕Less likely to help
Patients who have not undergone stem cell transplantation or do not exhibit symptoms of chronic graft-versus-host disease may not benefit from this research.
What this research studies
This research aims to develop and validate an artificial intelligence (AI) system that can accurately assess skin erythema, a key biomarker for chronic graft-versus-host disease (cGVHD), from photographs taken by patients. By leveraging a large database of over 11,000 images from diverse patient populations, the study seeks to create a reliable, efficient, and cost-effective tool for evaluating cGVHD, which is a significant complication following stem cell transplants. The AI technology will be tested against expert dermatologist assessments to ensure its accuracy and effectiveness in real-world settings.
Why it matters
Potential benefit: If successful, this research could provide a more accurate and accessible method for monitoring cGVHD, leading to improved patient outcomes and treatment validation.
How similar studies have gone: Previous research has shown promise in using AI for medical assessments, indicating that this approach could lead to significant advancements in the evaluation of cGVHD.
Where this research is happening
-
Vanderbilt University Medical Center
Nashville, United States Active
Researchers
- Principal investigator: Tkaczyk, Eric R — Vanderbilt University Medical Center
- Study coordinator: Tkaczyk, Eric R
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About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page.